Design of Multi-Epitope Vaccine for Staphylococcus saprophyticus: Pan-Genome and Reverse Vaccinology Approach

Design of an Epitope-Based Vaccine Against MERS-CoV

Background and Objectives: Middle East Respiratory Syndrome (MERS) is a viral respiratory illness caused by a coronavirus called Middle East respiratory syndrome. In the current study, immunoinformatics studies were applied to design an epitope-based vaccine construct against Middle East Respiratory Syndrome. Materials and Methods: In this study, epitopes base vaccine construct was designed against MERS using immunoinformatics approach. Results: In this approach, the targeted proteins were screened, and probable antigenic, non-allergenic, and good water-soluble epitopes were selected for vaccine construction. In vaccine construction, the selected epitopes were joined by GPGPG linkers, and a linear multi-epitope vaccine was constructed. The vaccine construct underwent a physiochemical property analysis. The 3D structure of the vaccine construct was predicted and subjected to refinement. After the refinement, the 3D model was subjected to a molecular docking analysis, TLRs (TLR-3 and TLR-9) were selected as receptors for vaccine construct, and the molecular docking analysis study determined that the vaccine construct has binding ability with the targeted receptor. Conclusions: The docking analysis also unveils that the vaccine construct can properly activate immune system against the target virus however experimental validation is needed to confirm the in silico findings further.

Molecular dynamics simulation and purification of chimeric L1/L2 protein from human papillomavirus type 52 expressed in Escherichia coli BL21 (DE3)

The available prophylactic vaccines for human papillomavirus (HPV) in the market are only effective against specific types of HPV, rendering them ineffective for other types of HPV infections. The objective of this research is to investigate the stability of the recombinant protein constructed, namely chimeric L1/L2 protein from HPV type 52, with improved cross-neutralization ability. The 3D model, predicted using Alphafold, Robetta, I-Tasser, and refined with Galaxy Refinement, is validated using Ramachandran plot analysis. The stability is verified through molecular dynamics simulations, considering parameters such as RMSD, RMSF, Rg, and SASA, where stable conditions are observed. The chimeric L1/L2 protein from HPV type 52 is purified using affinity chromatography, and the His-tag is cleaved using SUMO protease to obtain pure chimeric protein with the size of ~ 55 kDa. Western blot analysis confirms binding to anti-L1 HPV type 52 polyclonal antibody. The obtained vaccine candidate can be utilized as an effective prophylactic vaccine against HPV.

A novel vaccine construct against Zika virus fever: insights from epitope-based vaccine discovery through molecular modeling and immunoinformatics approaches

The Zika virus (ZIKV) is an emerging virus associated with the Flaviviridae family that mainly causes infection in pregnant women and leads to several abnormalities during pregnancy. This virus has unique properties that may lead to pathological diseases. As the virus has the ability to evade immune response, a crucial effort is required to deal with ZIKV. Vaccines are a safe means to control different pathogenic infectious diseases. In the current research, a multi-epitope-based vaccination against ZIKV is being designed using in silico methods. For the epitope prediction and prioritization phase, ZIKV polyprotein (YP_002790881.1) and flavivirus polyprotein (>YP_009428568.1) were targeted. The predicted B-cell epitopes were used for MHC-I and MHC-II epitope prediction. Afterward, several immunoinformatics filters were applied and nine (REDLWCGSL, MQDLWLLRR, YKKSGITEV, TYTDRRWCF, RDAFPDSNS, KPSLGLINR, ELIGRARVS, AITQGKREE, and EARRSRRAV) epitopes were found to be probably antigenic in nature, non-allergenic, non-toxic, and water soluble without any toxins. Selected epitopes were joined using a particular GPGPG linker to create the base vaccination for epitopes, and an extra EAAAK linker was used to link the adjuvant. A total of 312 amino acids with a molecular weight (MW) of 31.62762 and an instability value of 34.06 were computed in the physicochemical characteristic analysis, indicating that the vaccine design is stable. The molecular docking analysis predicted a binding energy of -329.46 (kcal/mol) for TLR-3 and -358.54 (kcal/mol) for TLR-2. Moreover, the molecular dynamics simulation analysis predicted that the vaccine and receptor molecules have stable binding interactions in a dynamic environment. The C-immune simulation analysis predicted that the vaccine has the ability to generate both humoral and cellular immune responses. Based on the design, the vaccine construct has the best efficacy to evoke immune response in theory, but experimental analysis is required to validate the in silico base approach and ensure its safety.

An In Silico Multi-epitopes Vaccine Ensemble and Characterization Against Nosocomial Proteus penneri

Proteus penneri (P. penneri) is a bacillus-shaped, gram-negative, facultative anaerobe bacterium that is primarily an invasive pathogen and the etiological agent of several hospital-associated infections. P. penneri strains are naturally resistant to macrolides, amoxicillin, oxacillin, penicillin G, and cephalosporins; in addition, no vaccines are available against these strains. This warrants efforts to propose a theoretical based multi-epitope vaccine construct to prevent pathogen infections. In this research, reverse vaccinology bioinformatics and immunoinformatics approaches were adopted for vaccine target identification and construction of a multi-epitope vaccine. In the first phase, a core proteome dataset of the targeted pathogen was obtained using the NCBI database and subjected to bacterial pan-genome analysis using bacterial pan-genome analysis (BPGA) to predict core protein sequences which were then used to find good vaccine target candidates. This identified two proteins, Hcp family type VI secretion system effector and superoxide dismutase family protein, as promising vaccine targets. Afterward using the IEDB database, different B-cell and T-cell epitopes were predicted. A set of four epitopes "KGSVNVQDRE, NTGKLTGTR, IIHSDSWNER, and KDGKPVPALK" were chosen for the development of a multi-epitope vaccine construct. A 183 amino acid long vaccine design was built along with "EAAAK" and "GPGPG" linkers and a cholera toxin B-subunit adjuvant. The designed vaccine model comprised immunodominant, non-toxic, non-allergenic, and physicochemical stable epitopes. The model vaccine was docked with MHC-I, MHC-II, and TLR-4 immune cell receptors using the Cluspro2.0 web server. The binding energy score of the vaccine was - 654.7 kcal/mol for MHC-I, - 738.4 kcal/mol for MHC-II, and - 695.0 kcal/mol for TLR-4. A molecular dynamic simulation was done using AMBER v20 package for dynamic behavior in nanoseconds. Additionally, MM-PBSA binding free energy analysis was done to test intermolecular binding interactions between docked molecules. The MM-GBSA net binding energy score was - 148.00 kcal/mol, - 118.00 kcal/mol, and - 127.00 kcal/mol for vaccine with TLR-4, MHC-I, and MHC-II, respectively. Overall, these in silico-based predictions indicated that the vaccine is highly promising in terms of developing protective immunity against P. penneri. However, additional experimental validation is required to unveil the real immune response to the designed vaccine.

Changes of microbiota level in urinary tract infections: A meta-analysis

No consensus has been reached on the dysbiosis signs of microbiota in patients with urinary tract infections (UTIs). This meta-analysis aimed to verify the relationship between microbiota levels and UTIs. PubMed, Web of Science, and Embase databases were retrieved for related articles published from inception until October 20, 2021. The standardized mean difference (SMD) and its related 95% confidence intervals (CIs) of the microbiota diversity and abundance were pooled under a random-effects model. Twelve studies were included in this meta-analysis. The pooled analysis revealed that the microbiota diversity was lower in patients with UTIs than in healthy individuals (SMD = -0.655, 95% CI = -1.290, -0.021, I ² = 81.0%, P = 0.043). The abundance of specific bacteria was higher in UTI subjects compared with healthy control individuals (SMD = 0.41, 95% CI = 0.07-0.74, P = 0.017), especially in North America patients with UTIs. Similar results were also found in studies with the total sample size being greater than 30. Importantly, Escherichia coli levels were increased in patients with UTI, whereas Lactobacillus levels decreased. E. coli and Lactobacilli have huge prospects as potential microbiota markers in the treatment of UTIs.

Immunoproteomic and immunoinformatic approaches identify secreted antigens and epitopes from Staphylococcus saprophyticus

Urinary tract infections (UTIs) are common human infections that compromise women's health around the world, even though they can affect men and women of all ages. Bacterial species are the primary causative agents of UTIs, while Staphylococcus saprophyticus, a gram-positive bacterium, is especially important for uncomplicated infections in young women. Despite the number of antigenic proteins identified in Staphylococcus aureus and other bacteria of the genus, there is no immunoproteomic study in S. saprophyticus. In this context, since pathogenic microorganisms secrete important proteins that interact with hosts during infection, the present work aims to identify the exoantigens from S. saprophyticus ATCC 15305 by immunoproteomic and immunoinformatic approaches. We identified 32 antigens on the exoproteome of S. saprophyticus ATCC 15305 by immunoinformatic tools. By using 2D-IB immunoproteomic analysis, it was possible to identify 3 antigenic proteins: transglycosylase IsaA, enolase and the secretory antigen Q49ZL8. In addition, 5 antigenic proteins were detected by immunoprecipitation (IP) approach, where the most abundant were bifunctional autolysin and transglycosylase IsaA proteins. The transglycosylase IsaA was the only protein detected by all the tools approaches used in this study. In this work it was possible to describe a total of 36 S. saprophyticus exoantigens. Immunoinformatic analysis allowed the identification of 5 exclusive linear B cell epitopes from S. saprophyticus and 5 epitopes presenting homology with other bacteria that cause UTIs. This work describes, for the first time, the profile of exoantigens secreted by S. saprophyticus and can contribute to the identification of new diagnostic targets of UTIs, as well as to develop vaccines and immunotherapies against bacterial urinary infections.

Immuno-informatics profiling of monkeypox virus cell surface binding protein for designing a next generation multi-valent peptide-based vaccine

Monkeypox is a viral etiological agent with hallmarks analogous to those observed in smallpox cases in the past. The ongoing outbreak of Monkeypox viral infection is becoming a global health problem. Multi-valent peptide based next generation vaccines provides us a promising solution to combat these emerging infectious diseases by eliciting cell-mediated and humoral immune response. Considering the success rate of subtractive proteomics pipeline and reverse vaccinology approach, in this study, we have developed a novel, next-generation, multi-valent, in silico peptide based vaccine construct by employing cell surface binding protein. After analyzing physiochemical and biological properties of the selected target, the protein was subjected to B cell derived T cell epitope mapping. Iterative scrutinization lead to the identification of two highly antigenic, virulent, non-allergic, non-toxic, water soluble, and Interferon-gamma inducer epitopes i.e. HYITENYRN and TTSPVRENY. We estimated that the shortlisted epitopes for vaccine construction, roughly correspond to 99.74% of the world’s population. UK, Finland and Sweden had the highest overall population coverage at 100% which is followed by Austria (99.99%), Germany (99.99%), France (99.98%), Poland (99.96), Croatia (99.93), Czech Republic (99.87%), Belgium (99.87), Italy (99.86%), China (97.83%), India (97.35%) and Pakistan (97.13%). The designed vaccine construct comprises of 150 amino acids with a molecular weight of 16.97242 kDa. Molecular docking studies of the modelled MEMPV (Multi-epitope Monkeypox Vaccine) with MHC I (PDB ID: 1I1Y), MHC II (PDB ID: 1KG0), and other immune mediators i.e. toll like receptors TLR3 (PDB ID: 2A0Z), and TLR4 (PDB ID: 4G8A) revealed strong binding affinity with immune receptors. Host immune simulation results predicted that the designed vaccine has strong potency to induce immune responses against target pathogen in the form of cellular and antibody-dependent immunity. Our findings suggest that the hypothesized vaccine candidate can be utilized as a potential therapeutic against Monkeypox however experimental study is required to validate the results and safe immunogenicity.